This invention relates to image sensors and in particular to image sensors that are useful in high speed processing of visual data.
Known image sensors include, for example, an imaging device comprised of a 512.times.512 matrix array of picture elements ("pixels"). Each pixel of the sensor may be a small photo cell disposed at an individual pixel location and arranged to produce an individual signal directly related to the amount of light falling on that pixel location. In operation, the individual pixels are accessed seriatim, to provide a series of individual pixel signals, each representing the amount of light falling on one pixel. These individual signals are digitized, to provide a series of digital words representing the light at the individual pixels. Assuming that each picture element can be read out (sensed or accessed) in 100 nanoseconds, approximately 33 milliseconds are needed to read out one entire frame, i.e., to read out all 262,144 pixels in the 512.times.512 array. The individual readout of each pixel of the sensor and the processing of its signal provides a high resolution scan of an image being viewed. However, in many high speed operations, the sequential, one-at-a-time, readout of each and every pixel of the sensor takes too long. That is, much time is taken to read out the contents of each and every pixel and, in addition, this results in the acquisition of a large amount of data, much of which may not be needed.
By way of example, consider the industrial task of inspecting bottles which are passing through a high speed filling line at a rate of 1,500 bottles per minute. At that rate, there is a period of 40 milliseconds to inspect each bottle. If, for example, an imaging device comprised of 512.times.512 pixels is used to inspect the bottles and if it takes approximately 33 milliseconds to read out one frame of the imaging device, there may not be sufficient time to process the information and to respond appropriately to the dynamic situation. That is, where the 512.times.512 system is operated conventionally, 262,244 samples of information will have to be sensed and processed in each frame. Even the most powerful computers cannot sort through this large amount of data fast enough to accomplish the necessary tasks required of the information and control system.
In many instances there is no need or interest in the information contained in each and every one of the 262,244 pixels. Rather, only a particular portion of the imager information may be of interest. It has been the practice heretofore to process the digitized data, after data acquisition, to discard unnecessary data. Thus, the digital words representing unimportant pixel signals may be discarded or else averaged to provide lower resolution signals representing unimportant portions of the image. For example, where the system is intended to recover data defining a relatively small object, the system may generate superpixel signals representing the background and retain only the data representing the object. Algorithms for automatically determining which pixel signals should be discarded or averaged to superpixel signals and which should be retained as individual pixel signals are known in the data processing art. These schemes can effectively reduce the data to be processed in subsequent steps. However, they do not solve the fundamental problem of data acquisition. Thus, the rate at which the system can take in new data is still limited by the frame rate of the sensor, i.e., by the time required to access and digitize all of the individual pixel signals. In such event much time will have been wasted in sensing undesired information and much time, effort and power will have been wasted processing the undesired information.
The problem discussed above will become more pronounced as production techniques improve, since the rates at which machines operate will increase and less response time will be available. Also as image sensors become larger, the amount of information to be handled will increase correspondingly. The problem becomes critical when a task which lends itself to machine vision control cannot be performed because of these limitations.